Search Results for author: Ahmed Khalifa

Found 28 papers, 14 papers with code

Learning Controllable Content Generators

1 code implementation6 May 2021 Sam Earle, Maria Edwards, Ahmed Khalifa, Philip Bontrager, Julian Togelius

It has recently been shown that reinforcement learning can be used to train generators capable of producing high-quality game levels, with quality defined in terms of some user-specified heuristic.

Game Mechanic Alignment Theory and Discovery

no code implementations20 Feb 2021 Michael Cerny Green, Ahmed Khalifa, Philip Bontrager, Rodrigo Canaan, Julian Togelius

We present a new concept called Game Mechanic Alignment theory as a way to organize game mechanics through the lens of systemic rewards and agential motivations.

Deep Learning for Procedural Content Generation

no code implementations9 Oct 2020 Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios N. Yannakakis, Julian Togelius

This article surveys the various deep learning methods that have been applied to generate game content directly or indirectly, discusses deep learning methods that could be used for content generation purposes but are rarely used today, and envisages some limitations and potential future directions of deep learning for procedural content generation.

Mixed-Initiative Level Design with RL Brush

1 code implementation6 Aug 2020 Omar Delarosa, Hang Dong, Mindy Ruan, Ahmed Khalifa, Julian Togelius

This paper introduces RL Brush, a level-editing tool for tile-based games designed for mixed-initiative co-creation.

Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network

1 code implementation11 Jul 2020 Matthew C. Fontaine, Ruilin Liu, Ahmed Khalifa, Jignesh Modi, Julian Togelius, Amy K. Hoover, Stefanos Nikolaidis

Generative adversarial networks (GANs) are quickly becoming a ubiquitous approach to procedurally generating video game levels.

Multi-Objective level generator generation with Marahel

1 code implementation17 May 2020 Ahmed Khalifa, Julian Togelius

This paper introduces a new system to design constructive level generators by searching the space of constructive level generators defined by Marahel language.

Mech-Elites: Illuminating the Mechanic Space of GVGAI

no code implementations11 Feb 2020 Megan Charity, Michael Cerny Green, Ahmed Khalifa, Julian Togelius

This paper introduces a fully automatic method of mechanic illumination for general video game level generation.

Mario Level Generation From Mechanics Using Scene Stitching

no code implementations7 Feb 2020 Michael Cerny Green, Luvneesh Mugrai, Ahmed Khalifa, Julian Togelius

This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes" that contain specific mechanics, using mechanic-sequences from agent playthroughs as input specifications.

Rotation, Translation, and Cropping for Zero-Shot Generalization

1 code implementation27 Jan 2020 Chang Ye, Ahmed Khalifa, Philip Bontrager, Julian Togelius

Deep Reinforcement Learning (DRL) has shown impressive performance on domains with visual inputs, in particular various games.


PCGRL: Procedural Content Generation via Reinforcement Learning

6 code implementations24 Jan 2020 Ahmed Khalifa, Philip Bontrager, Sam Earle, Julian Togelius

We investigate how reinforcement learning can be used to train level-designing agents.

Bootstrapping Conditional GANs for Video Game Level Generation

no code implementations3 Oct 2019 Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green, Niels Justesen, Sebastian Risi, Julian Togelius

Theresults demonstrate that the new approach does not only gen-erate a larger number of levels that are playable but also gen-erates fewer duplicate levels compared to a standard GAN.

Image Generation

Automatic Critical Mechanic Discovery Using Playtraces in Video Games

no code implementations6 Sep 2019 Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Tiago Machado, Julian Togelius

In a user study, human-identified mechanics are compared against system-identified critical mechanics to verify alignment between humans and the system.

Procedural Content Generation through Quality Diversity

1 code implementation9 Jul 2019 Daniele Gravina, Ahmed Khalifa, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis

Quality-diversity (QD) algorithms search for a set of good solutions which cover a space as defined by behavior metrics.

General Video Game Rule Generation

no code implementations12 Jun 2019 Ahmed Khalifa, Michael Cerny Green, Diego Perez-Liebana, Julian Togelius

We introduce the General Video Game Rule Generation problem, and the eponymous software framework which will be used in a new track of the General Video Game AI (GVGAI) competition.

Two-step Constructive Approaches for Dungeon Generation

no code implementations11 Jun 2019 Michael Cerny Green, Ahmed Khalifa, Athoug Alsoughayer, Divyesh Surana, Antonios Liapis, Julian Togelius

This paper presents a two-step generative approach for creating dungeons in the rogue-like puzzle game MiniDungeons 2.

ELIMINATION from Design to Analysis

no code implementations15 May 2019 Ahmed Khalifa, Dan Gopstein, Julian Togelius

Elimination is a word puzzle game for browsers and mobile devices, where all levels are generated by a constrained evolutionary algorithm with no human intervention.

Intentional Computational Level Design

1 code implementation18 Apr 2019 Ahmed Khalifa, Michael Cerny Green, Gabriella Barros, Julian Togelius

The procedural generation of levels and content in video games is a challenging AI problem.

Tree Search vs Optimization Approaches for Map Generation

5 code implementations27 Mar 2019 Debosmita Bhaumik, Ahmed Khalifa, Michael Cerny Green, Julian Togelius

We compare them on three different game level generation problems: Binary, Zelda, and Sokoban.

Global Optimization

Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning

3 code implementations4 Feb 2019 Arthur Juliani, Ahmed Khalifa, Vincent-Pierre Berges, Jonathan Harper, Ervin Teng, Hunter Henry, Adam Crespi, Julian Togelius, Danny Lange

Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment.

Atari Games Board Games

A Continuous Information Gain Measure to Find the Most Discriminatory Problems for AI Benchmarking

1 code implementation9 Sep 2018 Matthew Stephenson, Damien Anderson, Ahmed Khalifa, John Levine, Jochen Renz, Julian Togelius, Christoph Salge

This paper introduces an information-theoretic method for selecting a subset of problems which gives the most information about a group of problem-solving algorithms.

Generating Levels That Teach Mechanics

1 code implementation18 Jul 2018 Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Andy Nealen, Julian Togelius

The automatic generation of game tutorials is a challenging AI problem.

Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation

1 code implementation28 Jun 2018 Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, Sebastian Risi

However, when neural networks are trained in a fixed environment, such as a single level in a video game, they will usually overfit and fail to generalize to new levels.

Dimensionality Reduction

Talakat: Bullet Hell Generation through Constrained Map-Elites

no code implementations12 Jun 2018 Ahmed Khalifa, Scott Lee, Andy Nealen, Julian Togelius

We describe a search-based approach to generating new levels for bullet hell games, which are action games characterized by and requiring avoidance of a very large amount of projectiles.

"Press Space to Fire": Automatic Video Game Tutorial Generation

no code implementations30 May 2018 Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Julian Togelius

We propose the problem of tutorial generation for games, i. e. to generate tutorials which can teach players to play games, as an AI problem.

General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms

1 code implementation28 Feb 2018 Diego Perez-Liebana, Jialin Liu, Ahmed Khalifa, Raluca D. Gaina, Julian Togelius, Simon M. Lucas

In 2014, The General Video Game AI (GVGAI) competition framework was created and released with the purpose of providing researchers a common open-source and easy to use platform for testing their AI methods with potentially infinity of games created using Video Game Description Language (VGDL).


no code implementations9 May 2017 Ahmed Khalifa, Gabriella A. B. Barros, Julian Togelius

DeepTingle is a text prediction and classification system trained on the collected works of the renowned fantastic gay erotica author Chuck Tingle.

General Classification Translation

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